bge-small-en-v1.5

Model · Feature extraction

jina-embeddings-v2-small-en

Jina AI

The easiest way to starting using jina-embeddings-v2-small-en is to use Jina AI's Embedding API. jina-embeddings-v2-small-en is an English, monolingual embedding model supporting 8192 sequence length. It is based on a BERT architecture (JinaBERT) that supports the symmetric bidirectional variant of ALiBi to allow longer sequence length. The backbone jina-bert-v2-small-en is pretrained on the C4 dataset. The model is further trained on Jina AI's collection of more than 400 millions of sentence pairs and hard negatives. These pairs were obtained from various domains and were carefully selected through a thorough cleaning process. The embedding model was trained using 512 sequence length, but…

Model · Feature extraction

starwell

Charles Norton

Starwell is a generative model for stellarator design. Given a number of field periods, an aspect ratio and a target magnetic-gradient scale length LgradB, it samples a plasma boundary for the mhdstable problem of the ConStellaration benchmark, predicts its benchmark metrics, and lays out modular coils for it. Boundaries are SurfaceRZFourier dicts (rcos, zsin) that constellaration evaluates directly; sample also takes tau, guidance, steps and seed, and model.config.sampling holds the integrator's defaults. Coils are simsopt CurveXYZFourier coefficients for one half period with their currents, and simsopt.field.coilsviasymmetries builds the full set; limits (in metres and per metre) sets the…

Model · Feature extraction

Corpus-ViT

Gugu8

A vision encoder with a runtime-selectable token budget, built to sit between an image and an LLM. A coarse 32px grid covers the whole image; a router spends extra 16px detail only on the regions that need it. Output length is 49 + 3k tokens — 49 at k=0, 121 at k=24 — so you choose the tokens/fidelity trade-off per image, at inference, with no retraining. 24.94M parameters. Trained in 6000 steps (~30 min) on 2× Kaggle T4 by distillation from google/siglip-base-patch16-224 (86M). This is a working, honest baseline, not a competitive encoder. On the Flickr30k official test split it reaches 8.95 mean R@1 against the teacher's 83.25 — roughly 10% of its teacher. Chance on 1000 images is 0.10.…

Model · Feature extraction

jano-tts

Jano

This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Model · Feature extraction

ToarimEmbedder

Manuel Antonio Camacho Reyes

TóarimEmbedder es una arquitectura algorítmica de embeddings con estado (stateful) diseñada específicamente para resolver la amnesia contextual y la pérdida de continuidad en sistemas de Recuperación Aumentada por Generación (RAG) aplicados a corpus técnicos extensos y altamente regulados (manuales de maquinaria pesada, compendios normativos, bitácoras operativas y expedientes legales). A diferencia de los modelos basados en Transformers convencionales con atención densa cuadrática $O(n^2)$, TóarimEmbedder opera con complejidad lineal $O(n)$ en procesadores convencionales (CPU), permitiendo a las organizaciones indexar internamente su propiedad intelectual de forma ágil, blindando sus…

Model · Feature extraction

bge-small-zh-v1.5

Beijing Academy of Artificial Intelligence

More details please refer to our Github: FlagEmbedding. FlagEmbedding can map any text to a low-dimensional dense vector which can be used for tasks like retrieval, classification, clustering, or semantic search. And it also can be used in vector databases for LLMs. Updates - 10/12/2023: Release LLM-Embedder, a unified embedding model to support diverse retrieval augmentation needs for LLMs. Paper:fire: - 09/15/2023: The technical report of BGE has been released - 09/15/2023: The masive training data of BGE has been released - 09/12/2023: New models: - 09/07/2023: Update fine-tune code: Add script to mine hard negatives and support adding instruction during fine-tuning. - 08/09/2023: BGE…